I want to tell you about a statistic that changed my life and afterwards give you some thoughts about making your own data more life-changing. The stat was authored by my colleague Charles Fishman at Fast Company in his piece on the bottled water industry.
First let me give you some backstory: In San Francisco, the city water comes from Yosemite National Park. It’s so clean that the EPA doesn’t require San Francisco to filter it. And it’s cheap: San Francisco city water costs about .0021 cents per ounce. Meanwhile, bottled water costs about 7.9 cents per ounce. So obviously bottled water costs a lot more. But you knew that.
Now, let’s try a thought experiment. Let’s say you buy a bottle of Evian water for $1.35. You drink it and decide to reuse the bottle. Once a day, you fill it up with municipal water. Here’s the question: How many days could you refill that bottle before you would have racked up $1.35 in water charges from San Francisco? You could refill it once per day for 10 years, 5 months and 21 days.
When I read that, my brain exploded. And my purchases of bottled water have probably gone down 80%. Here’s what’s interesting to me: Fishman’s thought experiment isn’t adding any data to these two original statistics. He’s adding drama and depth by putting them in a real-life context. And that’s the fundamental strategy needed to make numbers stick: To drag them within the grasp of our intuition.
Here’s a more business-oriented example. For instance, years ago, Cisco Systems was deciding whether to install a wireless network for its employees. (That’s a "duh" decision today but not at the time.) The network would cost roughly $500 per year per employee to maintain. Is that worth it? Maybe yes, maybe no – we don’t have any strong intuition about $500 yearly expenses.
One employee did something to activate intuition. He figured out that if the wireless network could save the average employee 1 to 2 minutes per day, it would be a good investment. Suddenly, that’s a problem we can think about. Can we imagine a situation where the network might save someone 2 minutes? Almost certainly yes. (Whereas if the network had required 52 minutes of daily savings, that would have been a hard sell.) So bottom line: To make your data stick, you’ve got to drag it within the grasp of your audience’s intuition.
Chip and I wrote a Fast Company column, "The Gripping Statistic," about making numbers stick. There's also a long section on sticky data in the Credible chapter of Made to Stick. Here's a link to the Charles Fishman piece on bottled water that changed my drinking habits. When it comes to depicting data, there's only one place to turn: Edward Tufte's books, especially The Visual Display of Quantitative Information.